Number of tweets in different languages posted around Germany

There are many thing one can do with tweets (sentiment analysis, maps, …). This entry shows you how you can access the publicly available API using Java and how to analyse the data using R. For my purpose I am collecting geocoded  tweets around Germany. To collect the tweets I wrote a little java program (see below) which uses the twitter library twitter4J. This can be run on a machine in the background. Here is the java program which collects the tweets and stores them to disk. Except about 1 GB per week.

Collecting the geocoded tweets

Using this script I collected approx 1.3 Mio tweets in a weeks. The tweets are stored one line per tweet and one file per hour e.g. 2013-05-21T19_51_03.json. The content of the file would look like:

{"created_at":"Tue May 21 17:51:09 +0000 2013","id":336901993555709952,"id_str":"336901993555709952","text":"@OmegaBlue69 ... {"created_at":"Tue May 21 17:51:10 +0000 2013","id":336901996680450048,"id_str":"336901996680450048","text":"Sweet1 ....

Handling the json-file

The first task extracts the relevant information from these files. The following script reads the json files line by line and writes the coordinates, languages and for each tweet to a text-file e.g. “2013-05-21T19_51_03.coords.txt” using rjson.

Putting it all together

The next script picks up all text files with coordinate information, merges infrequent levels and does the color-coding. Finally it creates a simple barplot and stores the data in a data.frame all.data and the colors in a vector cols
In another blog I describe how this data can be used to create a zoomable map.